What Are Stacked Bar Charts, and When Should You Use Them?

Charts and graphs are an excellent way to make data easier to understand. However, visualizations can easily be misleading if they don’t suit the task at hand, so it’s important to learn the strengths and weaknesses of each. As a less widely used option, the stacked bar chart is a little understood but helpful choice.

What Is a Stacked Bar Chart?

Stacked bar charts break each category in a standard bar chart into smaller subcategories. Each bar is split into several differently colored sections to showcase how various parts make up the whole — similar to a pie chart.

Consider this example showing the revenue of Indian mining conglomerate Vedanta. The overall bars depict how the corporation’s income has changed over the years, while the subcategories showcase how each business segment contributes to that total.

Advantages of Stacked Bar Charts

A stacked bar chart can be an ideal way to display information in some scenarios. Learning its advantages will help you make the best visualization choice for your data. 

Breaking Down Complex Information

Stacked bar charts make it easier to understand complex data in context. Visual information is vital for quick decision-making, and a stacked graph supports that by combining multiple factors into a single illustration. Depending on the context, it can turn at least two visualizations — a bar graph and a pie chart — into one.

Take this chart comparing the features of different systematic review programs, for example. A conventional bar graph would show the same x-axis values, but it would require additional explanation for what those features are. By using a stacked chart instead, the study avoids the need for another paragraph or additional charts while showing the same information.

Obvious Outliers

Another benefit of stacked bar charts is that they make statistical outliers easier to spot. Sometimes, the overall value of a category may not change much between examples, but its specific buildup does. Those differences are more apparent in a stacked graph.

Using the above example, Revman Web’s relatively small number of appraisal features stands out. While its overall x-axis value isn’t unusual, the medium-shade blue section on the bar is far smaller than those around it. As a result, users can quickly infer that while Revman Web’s total feature count is standard, it doesn’t offer many appraisal solutions.

Visual Interest

It’s also worth considering that a stacked bar chart is visually appealing. Because people don’t come across these visualizations as much, seeing one immediately draws their eyes. That attention-grabbing factor helps websites boost session times and engagement.

Average attention spans have shortened to just 47 seconds over the years. As that figure keeps waning, websites must do more to capture visitor’s interest quickly and keep it for as long as possible. A visual outlier like a not-often-seen graph is a great way to do so.

Disadvantages of Stacked Bar Charts

Like any data visualization, stacked bar charts have their fair share of downsides, too. Businesses must consider these alongside the advantages to make the best decisions about how to display information.

Possible Confusion

As helpful as a stacked bar chart can be, its uniqueness comes at a cost. Users may not know how to interpret them. One of the most common confusions around these visualizations centers around the y-axis. It may be unclear if all segments within a bar start from the same zero baseline on the y-axis or if they begin where the one under them ends.

Negative values throw additional complications into things. Stacked bars going both ways up and down a y-axis make it hard to compare and interpret the subcategories within them.

These interpretation concerns are particularly pressing in a business context. Poor-quality data — which includes misleading information portrayals — costs organizations $12.9 million annually.

Difficult Comparisons for Smaller Subcategories

Similarly, stacked graphs can make comparisons difficult if subcategory values are small enough. Contrast between a whole’s individual components is one of these chart’s strongest advantages, but that goes away when these parts don’t seem as different as they are.

The nature of stacked bars means the upper categories will not start as the same baseline. This makes it hard to compare the relative sizes of the higher-level sections. Consequently, when the values in smaller subcategories do not vary as much as the larger ones, they appear the same. 

When to Use a Stacked Bar Chart

Given these pros and cons, these graphs work well in some situations but not others. In general, a stacked bar chart is best when comparing both totals and the totals’ makeup, but the overall figure is the most important factor.

In some cases, the individual components of the total are the focus rather than the whole. A pie chart or combined bar graph will be better here. Similarly, alternatives are preferable when there are a large number of subcategories or these parts show little variation. By contrast, stacked bar charts are ideal when the individual components have more variety, especially when this variation impacts the total. 

Data professionals can experiment with a few alternatives to see what works best for their data. Remember, choosing the wrong format is one of the most common data visualization mistakes, so these choices deserve attention. 

Stacked Bar Chart Best Practices

Like all graphs, stacked bar charts are most effective when they stick to a few best practices. Following these principles will minimize confusion and maximize the benefits.

Put the Most Important Information at the Bottom

One of the most important steps is to ensure each bar places its subcategories in the same position within the stack. This aids in easier comparisons. Beyond that, the most crucial category should be at the bottom of the bar.

The higher a component is in its bar, the harder it is to compare to others, as its baseline is affected by all categories below it. Consequently, any subcategory that’s more important to analyze than others should be at the bottom, where baselines are consistent.

Only Use a Few Subcategories

It’s also important to minimize the number of categories within each bar. While including a more detailed breakdown will present more information, it will also make more factors prone to misinterpretation. Too many sections will also crowd the chart, making it difficult to read.

How many subcategories qualifies as too many depends on the available space. Once sections become small enough that they show little variation or cannot contain numbers to clarify their value, there may be too much. Generally, a stacked bar chart is most effective with just three to four categories in each bar.

Use Contrasting Colors

Because stacked graphs can be challenging to read at first, designers should make each subcategory distinct from the rest. Contrasting colors are an excellent way to do this.

Viewers base first impressions on color roughly 90% of the time, so contrasting hues will enable faster distinctions than labels alone. These colors shouldn’t be bright to the point of straining the eyes, but they should clash enough to emphasize the difference between each subcategory.

Take Advantage of White Space

Similarly, stacked bar charts can use white space to further separate categories. A thin white line between each section will make them more distinct and easier to read. However, this blank space should be smaller than the y-axis increments to minimize disruption to baselines.

White space can also make the x-axis less crowded. Bars should be far enough apart to keep each overall category readable, but the blank space must be thinner than the bars themselves. 

Display Your Data the Right Way

Once you learn about stacked bar charts and where they’re most useful, you can use them to make data easier to understand. The more visualizations a business knows how to employ, the more tools they have for effective analysis. These design choices, in turn, fuel better decision-making and visitor retention.